This invention relates generally to the processing of image, sound or other correlated signals, and more particularly, to a method, apparatus, and article of manufacture for past and future motion classification.
Conventionally, error recovery has been achieved by correlation evaluation. For example, some recovery choices have been implemented using a conventional error pixel recovery method. Using neighboring data, spatial inclinations of the target data are detected. For example, the inclinations regarding four directions are evaluated according to the predetermined formulae which use the neighboring data. An interpolation filter is chosen where the inclination value, Ei, is the smallest among the four values calculated. In addition to the spatial inclination, a motion factor is also evaluated for error recovery. In the case of the motion area, a selected spatial filter is used for error recovery. On the other hand, the previous frame data at the same location as the target data typically are used for error recovery.
The conventional error recovery process discussed above may cause many serious degradations on changing data, especially on object edges. Actual signal distribution typically varies widely, so these problems are likely to occur. Therefore, there is a need for a way to restore a deteriorated signal to an undeteriorated signal which minimnizes degradations on changing data.
A method comprising determining a past motion class for target data, determining a future motion class for the target data, selecting one of the motion classes, and filtering the target data using the selected motion class is disclosed.